With the increasing scale and intelligence of engineering systems, traditional document-based development methods can no longer support the complex cross-domain collaboration and lifecycle-wide data consistency required. In complex system development, product design relies on efficient processes and collaborative industrial software. Model-Based Systems Engineering, as a systematic methodology, is becoming a core approach to supporting such processes. However, fragmentation and lack of interoperability among data models across industrial software present major obstacles to toolchain construction. To address this challenge, a unified Model-Based Systems Engineering data modeling architecture is required to integrate information flows throughout the product lifecycle and converge them into a digital thread. This paper focuses on the early stages of the conceptual and development phases, covering requirement analysis, functional definition, architecture design, verification and validation, and system simulation. A three-layer Model-Based Systems Engineering data modeling architecture is proposed, enabling the creation of a closed set of data models that form a continuous digital thread across development stages, connecting fragmented models from different industrial tools and providing consistent, end-to-end data support. A case study on a proton exchange membrane fuel cell system demonstrates the modeling practice and the resulting data model structure. The proposed approach has been applied to the T/DISA 1101-2025 MBSE Data Model and Exchange association standard, effectively supporting model integration and tool interoperability in projects and advancing the digitalization and standardization of complex system development.
Xu et al. (Wed,) studied this question.